Simcenter E-Machine Design
Fundamentals of Simcenter E-Machine Design
Software
Simcenter E-Machine Design 2312
Language
English
User Level
Beginner
Pricing ID
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List Price
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Contact us for private event pricing
Live In-Person Duration
1.5 Days
Live Online Duration
4 hours each day for 3 Days
This course will equip you with the a basic understanding of Simcenter E-Machine Design and will enable you to design and analyze solutions for any standard electric machine type. This includes synchronous, induction, switched reluctance, and brush-commutated radial flux machines as well as PM synchronous axial flux machines. It explains techniques for modifying geometry, setting windings, defining materials and viewing result.
WHO SHOULD ATTEND
The basic Simcenter E-Machine Design course is intended for engineers or analysts who are new to E-Machine simulation software, but it can also be used as refresher training for occasional users.
PROVIDED COURSE MATERIALS
- Student Guide
- Activity Material
PRIMARY COURSE TOPICS
Day 1
- Explore the GUI of Simcenter E-Machine Design and complete simple tasks using a default template for synchronous machines.
- Delve into template customization, geometry troubleshooting, and DXF integration within Simcenter E-Machine Design workflows.
- Explore how controls affect synchronous machine design, template parameter retention, and geometry visualization in Simcenter E-Machine Design
- Study winding configurations, connections, drive types, and layout customization in machine design, and learn validation metrics in Simcenter E-Machine Design.
- Navigate specs and operating points, comprehend rated current's significance, and utilize performance analysis charts to see advance angle effects.
Day 2
- The chapter discusses how to analyze charts, select display options for results, and understand different types of losses.
- We are inputting permeability data and data related to iron losses, conductivity / resistivity. Understand the impact of lamination thickness on loss calculations.
- Provide insights into modeling demagnetization in electric machines, focusing on data requirements, prediction methods, and analyzing its impact on performance.